A broad goal of the proposed research is to develop personal exposure monitors comprising wearable, wireless sensor arrays to detect harmful air pollutants within the breathing zone, and improve the assessment of causative exposure-dose-response relationships in epidemiological studies. Heterogeneous orthogonal detectors comprising functionalized carbon nanotube (CNT) based resonators will be designed and integrated with a smart phone platform, targeting the detection of ambient ozone (O3) in Phase 1, particulate matter, NOx and VOCs in Phase 2. Ozone not only influences climatic changes globally through greenhouse gas emissions, but also produces adverse health effects in humans as a secondary pollutant in urban smog through precursors generated in traffic and industrial pollution. As a powerful oxidant gas, O3 can elicit a range of physiological responses once inhaled, including reduced lung function and inflamed airways, exacerbating respiratory diseases such as asthma. Numerous research efforts address the relationship between ozone exposure and health outcomes including mortality and morbidity (hospitalizations, decrements in lung function, and asthma status), but due to lack of personal exposure data, considerable error may be introduced in assessing dose-response relationships. Currently, there are no existing sensors in the market suitable for real- time O3 exposure measurement within the breathing zone. Phase 1 research develops an ozone exposure detector array, fabricated using two classes of nanosensors: (a) polybutadiene polymer-functionalized CNT thin-films, (b) CNT thin-films decorated with Pt or Pd metallic nanoparticles. Both offer maximum sensitivity to ozone while reducing cross-sensitivity to interferents such as NOx. These detector films are integrated with compact radio-frequency (RF) resonators, which respond with unique resonance shift caused by molecular level gas adsorption on the film interface. In contrast to a chemiresistor, both amplitude and frequency shifts in this RF nanosensor may be used to minimize false positives for robust discrimination. Differential signaling between the primary sensor and a reference sensor (pure CNTs) compensates for environmental factors such as humidity, further improving selectivity. The differential signal is wirelessly interfaced through a microcontroller t a smart phone for data display of concentration levels and data communication to public health professionals or regulatory bodies via participatory and ubiquitous sensing. Additionally, sensors embedded in the mobile phone yield information on motion, physical activity, time stamp and GPS location of the subject that can be correlated to the exposure. A prototype O3 sensor will be developed and its performance characterized under controlled laboratory and ambient conditions. Field tests will be conducted on human volunteers to detect ambient ozone as a function of time over several days, and results compared directly with measurements made by standard badge samplers. Causative relationships will be explored by measuring eNO concentrations following the exposure, in collaboration with an environmental epidemiologist.